Peter Shaohua Deng

A note on the inventory models for deteriorating items with ramp type demand rate

Abstract In this research we study the inventory models for deteriorating items with ramp type demand rate. We first clearly point out some questionable results that appeared in (Mandal, B., Pal, A.K., 1998. Order level inventory system with ramp type demand rate for deteriorating items. Journal of Interdisciplinary Mathematics 1, 49–66 and Wu, K.S., Ouyang, L.Y., 2000. A replenishment policy for deteriorating items with ramp type demand rate (Short Communication). Proceedings of National Science Council ROC (A) 24, 279–286). And then resolve the similar problem by offering a rigorous and efficient method to derive the optimal solution. In addition, we also propose an extended inventory model with ramp type demand rate and its optimal feasible solution to amend the incompleteness in the previous work. Moreover, we also proposed a very good inventory replenishment policy for this kind of inventory model. We believe that our work will provide a solid foundation for the further study of this sort of important inventory models with ramp type demand rate.

Virus detection using data mining techinques

Malicious executables are computer programs, which may cause damages or inconveniences for computer users when they are executed. Virus is one of the major kinds of malicious programs, which attach themselves to others and usually get executed before the host programs. They can be easily planted into computer systems by hackers, or simply down loaded and executed by naive users while they are browsing the Web or reading e-mails. They often damage its host computer system, such as destroying data and spoiling system software when they are executed. Thus, to detect computer viruses before they get executed is a very important issue. Current detection methods are mainly based on pattern scanning algorithms. However, they are unable to detect unknown viruses. An automatic heuristic method to detect unknown computer virus based on data mining techniques, namely decision tree and naive Bayesian network algorithms, is proposed and experiments are carried to evaluate the effectiveness the proposed approach.

Real-time camera anomaly detection for real-world video surveillance

This paper proposes an automatic event detection technique for camera anomaly by image analysis, in order to confirm good image quality and correct field of view of surveillance videos. The technique first extracts reduced-reference features from multiple regions in the surveillance image, and then detects anomaly events by analyzing variation of features when image quality decreases and field of view changes. Event detection is achieved by statistically calculating accumulated variations along temporal domain. False alarms occurred due to noise are further reduced by an online Kalman filter that can recursively smooth the features. Experiments are conducted on a set of recorded videos simulating various challenging situations. Compared with an existing method, experimental results demonstrate that our method has high precision and low false alarm rate with low time complexity.

Intelligent automatic malicious code signatures extraction

The computer malicious executable code has been with us for a quite long time. Since computer hardware and Internet is growing so fast today, security threats of malicious executable code are getting more serious. Basically, malicious executable codes are categorized into three kinds. The first is called virus, which always infect other benign programs. The second is called Trojan which always masquerade its malicious executable code inside a usefully utility or freeware program. And the last but not the least is called worm that replicate and distribute itself automatically around the network. According to the literature survey [R.A. Grimes (2001)], current antivirus products cannot detect all the malicious codes, especially for those unseen, polymorphism malicious executable codes. Moreover, there are many virus program generators and mutation engines available on public Web sites that can be downloaded freely make a lot of unseen, polymorphism, and harmful executable malicious code. So how to extract virus signatures efficiently and effectively automatically instead of manually for an antivirus scanner system is quite important and also is the major purpose of this research.

Fitting Lanchester's square law to the Ardennes Campaign

In this research, we try to improve Brackens and Chens work to significantly better fit our extended Lanchester model into the Ardennes Campaign live data. Essentially, we adopt the concepts of the tactical factor variable and the shift time variable to improve the original Lanchesters model. Moreover, we use the Lanchester square law model instead of Lanchester linear law model to reflect the fact that the Ardennes Campaign was not an indirect-fire but a direct-fire combat. According to our numerical experimental result, we improved Brackens work by 39.26%, and Chens work by 19.51%. The contribution of this research is that we propose a much better qualitative analysis model for the explanation of modern combat.

Trace copy forgery detection for handwritten signature verification

Handwritten signature verification has been extensively studied in past decades. Its many applications include banking, credit card validation, security systems etc. We mainly deal with the trace copy forgery detection problem in a handwritten signature verification system. Based on one of our previously study [P. S. Deng et al. (1999)], we have proposed an efficient approach, called Dengs approach to build-up an offline handwritten signature verification system by using wavelet transformation technique. From the experimental results, the accuracy rate of the Dengs approach [P. S. Deng et al. (1999)] is 92.57% and 93.68% for English and Chinese respectively. The approach we proposed not only got a good accuracy result, i.e. 87%, but also has many other advantages as follows: (1) it can be applied in many languages including English and Chinese, (2) it can be adopted to both on-line and off-line applications, and (3) it uses all the strokes information rather than only the vertical strokes information in a Chinese signature.

Analysis of the ϵ-algorithm to accelerate the convergence

Abstract We study the ϵ-algorithm that was discussed in the papers of Guilpin et al. and Brezinski both published in 2004. Some researchers may motivate by their results to believe that is an efficient algorithm to generate many new series that will converge to the desired limit much faster than the original series. We will use the same example that appeared in Guilpin et al. to illustrate that some series derived by the ϵ-algorithm may not converge to the desired limit. Thus, we advise the researchers with care to look deeply into the existing literature before to use this sophisticated technique.

Analysis on comparison of distances derived by one-norm and two-norm with weight functions

Julian, Hung and Lin recently published a paper in Pattern Recognition Letters 33 (2012) 1219-1223 discussing the similarity measures of Mitchell (2003). However, after careful analysis we have found that the theorem in their paper is incomplete. In this paper, we will first point out the incomplete theorem. Second, we will provide a patch work to prove that the distance with the weighted function derived by one-norm is less than that derived by two-norm. Third, we will show that their original problem is only a corollary of Jensens inequality (1906). Our findings will help researchers develop more reasonable similarity measures and its application to pattern recognition under fuzzy intuitionistic set environment.

Algebraic method for EOQ Models with Temporary Sale Price

Abstract Recently, in order to introduce economic decision analysis to those younger students in school without the sophisticated knowledge of calculus, there have been more and more researchers devoting themselves to solving EOQ and EPQ models without derivatives. Wee et al. (2003) proposed an EOQ model with temporary sale price derived without using calculus. They used the standard method to complete the square to find the maximum point and maximum value for a quadratic function. We treat the same problem to avoid their lengthy computation and provide an efficient and succinct solution. Hence, the reader can absorb the knowledge of the inventory model clearer and easier.

Analytic inventory model with a mixture of back orders and lost sales

In this paper a precise approach is used to extend and analyze the article published by Padmanabhan and Vrat (1990) in the International Journal of Systems Science. Utilizing this approach, we develop a criterion for existence and uniqueness of the optimal solution of the total cost function. If the criterion cannot be satisfied, this model degenerate to an inventory model with one cycle. In such case, the article shows that a longer stock shortage time would lower the total cost. Therefore, we evaluate the cost variation under different allotted times to provide decision-makers with strategies to balance the time and cost. We present illustrations to demonstrate the exactness of this process.